A Review on Vibration-Based Condition Monitoring of Rotating Machinery

Abstract

Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal functioning states are related to specific patterns that can be extracted from vibration signals. Extensively studied issues concern the different methodologies used for carrying out the main phases (signal measurements, pre-processing and processing, feature selection, and fault diagnosis) of a malfunction automatic diagnosis. In addition, vibration-based condition monitoring has been applied to a number of different mechanical systems or components. In this review, a systematic study of the works related to the topic was carried out. A preliminary phase involved the analysis of the publication distribution, to understand what was the interest in studying the application of the method to the various rotating machineries, to identify the interest in the investigation of the main phases of the diagnostic process, and to identify the techniques mainly used for each single phase of the process. Subsequently, the different techniques of signal processing, feature selection, and diagnosis are analyzed in detail, highlighting their effectiveness as a function of the investigated aspects and of the results obtained in the various studies. The most significant research trends, as well as the main innovations related to the various phases of vibration-based condition monitoring, emerge from the review, and the conclusions provide hints for future ideas.

Towards Highly Efficient, Additively Manufactured Passive Vibration Eliminators for Mechanical Systems

“…However, it is not always possible to design a machine from scratch or significantly modify an already existing one. For this reason, methods to eliminate vibrations are being studied, not only for new structures, such as a frame for a delta robot [ 2 ], but also for existing ones [ 5 , 6 ]. Methods to suppress vibrations, as well as the negative effects caused by them, can be divided into three main groups: (i) active, (ii) passive, and (iii) semi-active, which is the combination of both active and passive methods [ 7 , 8 , 9 ].…”

Highly Reliable Multicomponent MEMS Sensor for Predictive Maintenance Management of Rolling Bearings

“…Metrological characterizations and suitable calibration procedures of sensors used in the monitoring networks are needed to guarantee the reliability of the measurements [ 20 ], providing high quality [ 21 ] and trustworthy information [ 22 ], ensuring a learning process based on reliable and accurate data [ 23 ]; moreover, in the case of sensor substitution, the calibration of data would allow to maintain the metrological traceability from sensor-to-sensor, ensuring the continuity of data-flow trustworthiness. Nevertheless, at present, suitable metrological calibration methods (traceable to the SI, International Systems of Units, and supported by detailed uncertainty budgets), can be applied only to ‘measuring instruments’, but not to ‘MEMS-based sensors’, since standard procedures are unavailable, and thus proper sensitivity parameters cannot be accurately identified.…”

Blade Fault Localization with the Use of Vibration Signals Through Artificial Neural Network: A Data-Driven Approach

“…With this approach, manual interpretation, which is only subject to the knowledge and the individual's experience, can be relegated. Furthermore, artificial intelligent methods offer automated fault diagnosis (Tiboni et al, 2022;Pang et al, 2020). Previous researchers had also used this method for blade fault diagnosis.…”